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of the Max Planck Society for the Advancement of Science. The Department of Machine Learning and Systems Biology, headed by director Prof. Dr. Karsten Borgwardt, is seeking a Postdoctoral Research Fellow (m/f
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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The University of British Columbia (UBC) | Vancouver UBC, British Columbia | Canada | about 1 month ago
team in the AI in Medicine Lab (www.aimlab.ca ). This position is based in the School of Biomedical Engineering. The successful candidate will work in the AI in Medicine Lab, applying machine learning
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). Strong background in stochastic optimization, machine learning, or mathematical statistics. Track record of publications in relevant journals/conferences (ICML,NeurIPS,ICLR,COLT, Siam Journals, JMLR, COAP
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design and implementation of visual cues detection on video datasets (face and gesture), context-aware multimodal analysis, machine learning/self-supervised learning for automatically detecting subtle
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the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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Biology, or a related field Solid foundation in cellular immunology or molecular biology Strong motivation to learn CAR T cell technologies and translational research approaches Excellent organizational
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical